Over the years, I've seen a rapid improvement in retail technology. One problem in retail today is the wait in a queue for people waiting to buy. This frustrates customers, leading to many lost sales.

Self-Checkout Technology

Self-checkout cash registers have become common in larger stores. Customers scan and bag their items and pay without a cashier. This retail innovation helps reduce queues and staffing needs, as one person can manage eight cash registers.

Benefits of self-checkout:

• Shorter wait times
• More checkout options during busy periods
• Reduced labour costs for retailers

Challenges with self-checkout:

• Some customers dislike using the technology, so you still need manned cash registers.
• These cash registers have high setup costs as they are expensive cash registers.
• It is not worth it for shops with low turnover.
• Higher rates of shoplifting. A recent study here of 5,000 transactions found that self-checkout lanes had 16 times higher shrinkage rates than traditional cashier lines. About 6.7% of self-checkout transactions had some amount of partial shrinkage versus just 0.32% with cashiers.

These are significant problems for retailers considering self-checkout technology. Several stores have removed their self-checkouts as a result. 

AI in Retail: The Next Frontier of Checkout

.One promising solution uses AI.

How AI-Powered Cashierless Stores Work

This "grab and go" approach eliminates the need for scanning, potentially reducing theft by automatically addressing shoplifting while creating a smoother checkout experience. I can see the potential here as someone who's worked closely with POS systems.

Conclusion

The retail landscape is changing. While queues and theft remain significant challenges, new technologies offer promising retail queue management and shrinkage prevention solutions. As a POS provider, we're committed to helping retailers of all sizes navigate this evolving terrain.

Have you experienced these new checkout technologies as a customer? What are your thoughts on the future of retail? If you are in Melbourne or Sydney, you can see it in operation where it is on trial at ten 7-Eleven Australia stores here: 

7-Eleven Cranbourne North (945 S. Gippsland Highway Cranbourne North)
7-Eleven Truganina (1/475 Leakes Road, Truganina Vic)
7-Eleven Craigieburn (264-270 Craigieburn Road Craigieburn Vic);
7-Eleven Doreen (8 Whitford Way Doreen Vic)
7-Eleven Tarneit (32 Escapade Street Tarneit Vic)
7-Eleven Braybrook (87 Ashley Street, Braybrook Vic)
7-Eleven Richmond (Building 2/658 Church Street, Cremorne Vic)
7-Eleven Burwood (Parramatta Road, Burwood, NSW)
7-Eleven Northmead (137 Windsor Road, Northmead NSW)
7-Eleven Graystanes (601 Great Western Highway, Greystanes NSW)

For people like us operating in a dynamic and competitive landscape, providing exceptional customer service and support is our key differentiator. So, our support team works hard to respond to client questions, troubleshoot issues, and ensure our point-of-sale (POS) software enables their success. So, when we heard about AI conversation bots that could potentially assist our support team, we were eager to test this emerging technology.

After developing our own AI chatbot prototype and trialling it on actual customer queries, we found there are indeed limitations with AI support today.

We feed it thousands of our customers' queries.

Depending on who accessed its answers, we got these disputed scores. I say disputed as some judges were much more negative than others. This is a consensus score, not an individual view.

- Approximately 23% of the chatbot responses were largely to wholly accurate. These tended to be the stuff that our support staff felt were things they knew well and would have little trouble doing without AI.

- 50% were partially correct but lacked vital details. 

- 15% were unclear due to poorly phrased customer questions. This is a common problem that those who ask questions in the real world to get accurate information need to know much. Rubbish in = Rubbish out.

- 10% were utterly wrong.

Our AI chatbot clearly has room for improvement before it goes live.

However, AI can still provide value when implemented correctly by augmenting our support team’s capabilities. 

Why AI struggles with complex support queries

Through our testing process, we gained insight into factors that limit AI chatbots’ capabilities for software support:

1. Insufficient training data

Like humans, AI systems require extensive ‘practice’ through training data to become highly skilled at specific tasks. Our prototype only had access to a thousand pre-recorded customer support calls from which to learn - this is far too little data to fully grasp the complexity and nuances of troubleshooting what is our system probably the most advanced POS software in Australia.

2. Incomplete understanding of context and ambiguity

Humans draw upon years of world knowledge and experience when interpreting language. AI chatbots currently lack this contextual awareness, so they struggle to clarify vague questions and handle ambiguities. Our clients have a range of English knowledge; some know plenty, we have clients with doctorates and some that barely speak English. So 15% of customer queries stumped our chatbot due to unclear wording that we could easily interpret.

3. Inability to grasp nuanced domain knowledge

POS software is feature-rich and built to handle intricate retailer needs. Most AI systems today would need explicit training to comprehend the industry-specific terminology, workflows, exceptions, integrations, and technical considerations involved. Without directly relevant domain training, the chatbot’s knowledge gaps led it to miss critical details in 50% of test cases.

Best practices for implementation

While the technology still has maturing to do, useful AI assistance is within reach by following guiding principles for implementation:

Ensure sufficient high-quality training data

For accurate learning, training datasets must cover each type of support scenario the AI may encounter. Data should be cleanly recorded without errors that could propagate misleading information. The problem here is that our information is real, and in the real world information with errors is common.

Provide ongoing human feedback.

Humans must continually verify and correct the AI’s responses, allowing its knowledge to evolve through feedback over months and years. This human-in-the-loop oversight is critical. This will take a lot of work.

The future role of AI in customer support

Though AI chatbots cannot wholly substitute for human support staff at this stage, we see bright possibilities for AI assistance going forward:

• Handling high volumes of repetitive queries - Freeing support staff to focus on higher-level, more complex problem-solving for customers.

• Providing 24/7 self-service - Enabling customers to access basic troubleshooting after hours when support staff are offline.

• Supporting human agents - Assisting our support staff with knowledge lookup, documentation, and tracing issues.

While AI support today is imperfect, we are excited by its prospects through careful implementation. Over the next several years, we aim to refine our chatbot to be an invaluable teammate for our human support staff - combining the best human and machine capabilities to deliver exceptional customer assistance. With a spirit of experimentation and patience, as this emerging technology matures, we know that AI promises to improve customer service.

Let me know if you are interested in learning more because this is really interesting stuff.

Our system has AI in, and were currently trying to extend it. Currently, as far as I know, we are the only ones in our market space with this type of advanced technology. As part of our research, we applied and were accepted into the Dall-E program. Part of what it does is draw computer pictures. This part excited us as it meant that even people with no skill in art could draw high-quality posters. This could be very useful for our clients.

Now a sister program to Dall-E, Midjourney made a picture that won first prize in a prestige art contest. A computer drew this.

What you do is enter some expression like a google search, and the program will draw a picture. admittedly this one, the *artist* made many attempts first.

Now I decided to test Dall-E by drawing some pictures showing you its capabilities. See what you think. I think it shows potential. An excellent graphic artist would charge you hundreds of dollars for something like this. If anyone wants me to demonstrate, let me know.

I decided to use "sunset over a paper shop with newspapers and magazines"

Here I decided to use "sunset over a pet shop with dogs, cats"

Then I decided to do some marketing images for posters.

So I said, "Father's day sale gifts."

Here is one I made for "Business internet network."

All pictures are in Hi-Res, so if you right-click and view the image to see the incredible detail. I think you will be impressed.

This is the future.

Imagine what it will do to the art industry.

Amazon has launched a new business to sell its 'Just Walk Out’ technology that it uses now in its cashier-less Amazon Go stores to other retailers and apparently many shops are interested. 

Some interesting points are that 

- the site has no pricing. 

- Support appears to be over phone and email. 

- Interestingly the setup and installation of the system are stated as a few weeks once Amazon has access to the retailer’s store, It seems like it requires a shop fit to work.

I can see why shop owners would be interested as they get rid of all queues and the cashiers that they have now. 

Assuming it is as good as they claim, I would not be surprised if in five (5) years we will be installing in most of our sites this technology.

Right now if you go into any shopping centre, you will see almost everyone is offering a buy now pay later(BNPL) option. There is little choice for many shops as Australians are dumping credit cards and going for them. Already more than a million Australians have stopped using credit cards and are using these services. So today BNPL startups are popping up like mushrooms in Australia, and although there are plenty of players in this market already, the interest now is that CBA bank has announced that it is moving in a big way into this market and soon I am sure the other banks will also move into this market.

Although each offering of BNPL is different, I think the following is a fair comment, unlike the credit card most of the fees are paid for by the merchant, not the customer. Most merchants that use these services do so because these services do push their stores thus increasing their sales.

The other issue is that a BNPL customer if you have the right products for them, is a good customer. Here is an analysis of a zip customer 

They buy more each time, and they buy more often, the operative point being here, do you have the products for these customers? 

So the big problem for many of my clients is that with credit cards whereas the fees are relatively small and can be either absorbed and/or charged to the client, with a  BNPL model, the costs are much higher, about 5% and it can be tough to charge this back to the customer as both the customers and the BNPL do not like it this chargeback. A hairdresser who was my client, charged a woman a surcharge because she used zip, the customer went on social media to complain, within hours zip picked it up the twitter and rang her and asked her to please explain. 

This leaves many of my clients with a problem, either give up a large number of clients and a major market or offer BNPL. The answer will be a decision for each store. 

If you do laybys, I do suggest that you switch at least for this service over to BNPL. If you do your sums, the extra costs and bother to you in laybys are just not worth this 5% fee.

If your layby customers do not have a BNPL account consider this when I did an experiment, I found that it took me about 2 minutes to get a BNPL account.  

Now assuming you do decide to go into this space well the question is which one do you use. Currently, there are two big ones, Afterpay and Zip. You can go for others but these two you need to look at first. Both are I think are reliable. Both run extensive marketing campaigns which do benefit the merchants that do use them. Both have a lot of followers. Generally users of these services, I find have both.

As a comparison, Zip big plus is that it lets you sell higher-priced items, its costs are a bit lower, and it pays faster. Plus it is easier to get, and they bug you less. Afterpay will put conditions on its use and in fact on all payment types that you use which blew my mind, if you have Afterpay in your shop, if you do a cash transaction you must abide by Afterpay conditions even though it has nothing to do with them. I have never seen Zip do anything like that. This is why I suggest if you are thinking of entering this market, try Zip first. Once you have bedded it down then look at others.

If you want to investigate more, click here.

PS Whatever you do, what you need to consider is that BNPL is clearly the future, soon I predict that all shops will need it.

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